Genetic legacies of mega-landslides: Cycles of isolation and contact across flank collapses in an oceanic island.

Catastrophic flank collapses are recognized as important drivers of insular biodiversity dynamics, through the disruption of species ranges and subsequent allopatric divergence. However, little empirical data supports this conjecture, with their evolutionary consequences remaining poorly understood. Using genome-wide data within a population genomics and phylogenomics framework, we evaluate how mega-landslides have impacted evolutionary and demographic history within a species complex of weevils (Curculionidae) within the Canary Island of Tenerife. We reveal a complex genomic landscape, within which individuals of single ancestry were sampled in areas characterized by long-term geological stability, relative to the timing of flank collapses. In contrast, individuals of admixed ancestry were almost exclusively sampled within the boundaries of flank collapses. Estimated divergence times among ancestral populations aligned with the timings of mega-landslide events. Our results provide first evidence for a cyclical dynamic of range fragmentation and secondary contact across flank collapse landscapes, with support for a model where this dynamic is mediated by Quaternary climate oscillations. The context within which we reveal climate and topography to interact cyclically through time to shape the geographic structure of genetic variation, together with related recent work, highlights the importance of topoclimatic phenomena as an agent of diversification within insular invertebrates.

Evaluation of a whole-exome sequencing pipeline and benchmarking of causal germline variant prioritizers.

Most causal variants of Mendelian diseases are exonic. Whole-exome sequencing (WES) has become the diagnostic gold standard, but causative variant prioritization constitutes a bottleneck. Here we assessed an in-house sample-to-sequence pipeline and benchmarked free prioritization tools for germline causal variants from WES data. WES of 61 unselected patients with a known genetic disease cause was obtained. Variant prioritizations were performed by diverse tools and recorded to obtain a diagnostic yield when the causal variant was present in the first, fifth, and 10th top rankings. A fraction of causal variants was not captured by WES (8.2%) or did not pass the quality control criteria (13.1%). Most of the applications inspected were unavailable or had technical limitations, leaving nine tools for complete evaluation. Exomiser performed best in the top first rankings, while LIRICAL led in the top fifth rankings. Based on the more conservative top 10th rankings, Xrare had the highest diagnostic yield, followed by a three-way tie among Exomiser, LIRICAL, and PhenIX, then followed by AMELIE, TAPES, Phen-Gen,  AIVar, and VarNote-PAT. Xrare, Exomiser, LIRICAL, and PhenIX are the most efficient options for variant prioritization in real patient WES data.

Climate drives community-wide divergence within species over a limited spatial scale: evidence from an oceanic island.

Geographic isolation substantially contributes to species endemism on oceanic islands when speciation involves the colonisation of a new island. However, less is understood about the drivers of speciation within islands. What is lacking is a general understanding of the geographic scale of gene flow limitation within islands, and thus the spatial scale and drivers of geographical speciation within insular contexts. Using a community of beetle species, we show that when dispersal ability and climate tolerance are restricted, microclimatic variation over distances of only a few kilometres can maintain strong geographic isolation extending back several millions of years. Further to this, we demonstrate congruent diversification with gene flow across species, mediated by Quaternary climate oscillations that have facilitated a dynamic of isolation and secondary contact. The unprecedented scale of parallel species responses to a common environmental driver for evolutionary change has profound consequences for understanding past and future species responses to climate variation.

Benchmarking of human Y-chromosomal haplogroup classifiers with whole-genome and whole-exome sequence data.

In anthropological, medical, and forensic studies, the nonrecombinant region of the human Y chromosome (NRY) enables accurate reconstruction of pedigree relationships and retrieval of ancestral information. Using high-throughput sequencing (HTS) data, we present a benchmarking analysis of command-line tools for NRY haplogroup classification. The evaluation was performed using paired Illumina data from whole-genome sequencing (WGS) and whole-exome sequencing (WES) experiments from 50 unrelated donors. Additionally, as a validation, we also used paired WGS/WES datasets of 54 individuals from the 1000 Genomes Project. Finally, we evaluated the tools on data from third-generation HTS obtained from a subset of donors and one reference sample. Our results show that WES, despite typically offering less genealogical resolution than WGS, is an effective method for determining the NRY haplogroup. Y-LineageTracker and Yleaf showed the highest accuracy for WGS data, classifying precisely 98% and 96% of the samples, respectively. Yleaf outperforms all benchmarked tools in the WES data, classifying approximately 90% of the samples. Yleaf, Y-LineageTracker, and pathPhynder can correctly classify most samples (88%) sequenced with third-generation HTS. As a result, Yleaf provides the best performance for applications that use WGS and WES. Overall, our study offers researchers with a guide that allows them to select the most appropriate tool to analyze the NRY region using both second- and third-generation HTS data.

Digging into the admixture strata of current-day Canary Islanders based on mitogenomes.

The conquest of the Canary Islands by Europeans began at the beginning of the 15th century and culminated in 1496 with the surrender of the aborigines. The collapse of the aboriginal population during the conquest and the arrival of settlers caused a drastic change in the demographic composition of the archipelago. To shed light on this historical process, we analyzed 896 mitogenomes of current inhabitants from the seven main islands. Our findings confirm the continuity of aboriginal maternal contributions and the persistence of their genetic footprints in the current population, even at higher levels (>60% on average) than previously evidenced. Moreover, the age estimates for most autochthonous founder lineages support a first aboriginal arrival to the islands at the beginning of the first millennium. We also revealed for the first time that the main recognizable genetic influences from Europe are from Portuguese and Galicians.

Bioinformatic approaches to draft the viral genome sequence of Canary Islands cases related to the multicountry mpox virus 2022-outbreak.

On July 23, 2022, monkeypox disease (mpox) was declared a Public Emergency of International Concern (PHEIC) by the World Health Organization (WHO) due to a multicountry outbreak. In Europe, several cases of mpox virus (MPXV) infection related to this outbreak were detected in the Canary Islands (Spain). Here we describe the combination of viral DNA sequencing and bioinformatic approaches, including methods for de novo genome assembly and short- and long-read technologies, used to reconstruct the first MPXV genome isolated in the Canary Islands on the 31st of May 2022 from a male adult patient with mild symptoms. The same sequencing and bioinformatic approaches were then validated with three other positive cases of MPXV infection from the same mpox outbreak. We obtained the best results using a reference-based approach with short reads, evidencing 46-79 nucleotide variants against viral sequences from the 2018-2019 mpox outbreak and placing the viral sequences in the new B.1 sublineage of clade IIb of the MPXV classification. This study of MPXV demonstrates the potential of metagenomics sequencing for rapid and precise pathogen identification.

From Samples to Germline and Somatic Sequence Variation: A Focus on Next-Generation Sequencing in Melanoma Research.

Next-generation sequencing (NGS) applications have flourished in the last decade, permitting the identification of cancer driver genes and profoundly expanding the possibilities of genomic studies of cancer, including melanoma. Here we aimed to present a technical review across many of the methodological approaches brought by the use of NGS applications with a focus on assessing germline and somatic sequence variation. We provide cautionary notes and discuss key technical details involved in library preparation, the most common problems with the samples, and guidance to circumvent them. We also provide an overview of the sequence-based methods for cancer genomics, exposing the pros and cons of targeted sequencing vs. exome or whole-genome sequencing (WGS), the fundamentals of the most common commercial platforms, and a comparison of throughputs and key applications. Details of the steps and the main software involved in the bioinformatics processing of the sequencing results, from preprocessing to variant prioritization and filtering, are also provided in the context of the full spectrum of genetic variation (SNVs, indels, CNVs, structural variation, and gene fusions). Finally, we put the emphasis on selected bioinformatic pipelines behind (a) short-read WGS identification of small germline and somatic variants, (b) detection of gene fusions from transcriptomes, and (c) de novo assembly of genomes from long-read WGS data. Overall, we provide comprehensive guidance across the main methodological procedures involved in obtaining sequencing results for the most common short- and long-read NGS platforms, highlighting key applications in melanoma research.

Developing CIRdb as a catalog of natural genetic variation in the Canary Islanders.

The current inhabitants of the Canary Islands have a unique genetic makeup in the European diversity landscape due to the existence of African footprints from recent admixture events, especially of North African components (> 20%). The underrepresentation of non-Europeans in genetic studies and the sizable North African ancestry, which is nearly absent from all existing catalogs of worldwide genetic diversity, justify the need to develop CIRdb, a population-specific reference catalog of natural genetic variation in the Canary Islanders. Based on array genotyping of the selected unrelated donors and comparisons against available datasets from European, sub-Saharan, and North African populations, we illustrate the intermediate genetic differentiation of Canary Islanders between Europeans and North Africans and the existence of within-population differences that are likely driven by genetic isolation. Here we describe the overall design and the methods that are being implemented to further develop CIRdb. This resource will help to strengthen the implementation of Precision Medicine in this population by contributing to increase the diversity in genetic studies. Among others, this will translate into improved ability to fine map disease genes and simplify the identification of causal variants and estimate the prevalence of unattended Mendelian diseases.

A benchmarking of human mitochondrial DNA haplogroup classifiers from whole-genome and whole-exome sequence data.

The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. We also assessed the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short-read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

Evaluation of Whole-Exome Enrichment Solutions: Lessons from the High-End of the Short-Read Sequencing Scale.

Whole-exome sequencing has become a popular technique in research and clinical settings, assisting in disease diagnosis and increasing the understanding of disease pathogenesis. In this study, we aimed to compare common enrichment capture solutions available in the market. Peripheral blood-purified DNA samples were enriched with SureSelectQXT V6 (Agilent) and various Illumina solutions: TruSeq DNA Nano, TruSeq DNA Exome, Nextera DNA Exome, and Illumina DNA Prep with Enrichment, and sequenced on a HiSeq 4000. We found that their percentage of duplicate reads was as much as 2 times higher than previously reported values for the previous HiSeq series. SureSelectQXT and Illumina DNA Prep with Enrichment showed the best average on-target coverage, which improved when off-target regions were included. At high coverage levels and in shared bases, these two solutions and TruSeq DNA Exome provided three of the best performances. With respect to the number of small variants detected, SureSelectQXT presented the lowest number of detected variants in target regions. When off-target regions were considered, its ability equalized to other solutions. Our results show SureSelectQXT and Illumina DNA Prep with Enrichment to be the best enrichment capture solutions.